Convolutional layers in a CNN may be used to extract features from an input image, or input feature map (IFM), by sliding a convolution kernel across the IFM. That is, one or more IFMs may be input to a convolutional layer and may be convolved using one or more sets of different filter (weight) kernels. The results of the convolutions are summed to generate an output feature map (OFM). The OFMs may then be used as IFMs for a next convolutional layer, and features may be further extracted by sliding a different set of convolution kernels across the IFMs.